Applying machine learning for optimization of dehumidification strategy on the modified model for the non-equilibrium condensation in steam turbines

DOI10.1016/j.enganabound.2022.09.013WikidataQ114183089 ScholiaQ114183089MaRDI QIDQ6137959

Mohsen Saffari Pour, Khosro Rezaee, Seyed Soheil Mousavi Ajarostaghi, Amir Momeni Dolatabadi

Publication date: 16 January 2024

Published in: Engineering Analysis with Boundary Elements (Search for Journal in Brave)

zbMATH Keywords

optimizationdehumidificationmachine learning (ML)suction techniquenon-equilibrium condensing

Mathematics Subject Classification ID

Biology and other natural sciences (92-XX) Fluid mechanics (76-XX)

Cites Work

• Effects of turbulence and inlet moisture on two-phase spontaneously condensing flows in transonic nozzles
• Simulation of stably stratified turbulent channel flow using residual-based variational multiscale method and isogeometric analysis
• Analysis of Lie symmetry, explicit series solutions, and conservation laws for the nonlinear time-fractional Phi-four equation in two-dimensional space

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